Summary statistics for the case-only (by sex and metastasis at diagnosis) and subgroup (by sex) Meta-analysis of the genome-wide association study of Ewing Sarcoma (Hubbard et al., Cell Genomics 2026)

Genome-wide association study (GWAS) meta-analysis summary statistics for case-only analysis of Ewing sarcoma patients by sex and metastasis and subgroup analysis by sex from Hubbard et al., “Genome-wide association study meta-analysis identifies susceptibility loci informing Ewing sarcoma etiology and potential mechanisms of risk,” Cell Genomics (2026). https://doi.org/10.1016/j.xgen.2026.101422 Contents: fixed-effects meta-analysis results (Metasoft) from studies and participants with covariates of interest (metastasis at diagnosis and sex). Methods summary: genotypes were imputed to the TOPMed r3 reference panel, See paper in Cell Genomics for full case-control study inclusion. Logistic regression under an additive model was run in PLINK 1.9, adjusting for study-specific principal components. Results were combined by fixed-effects meta-analysis in Metasoft. Metastasis Case only There were 268 cases with metastasis and 666 without metastasis at diagnosis included in the metastasis case only analysis. These cases were from the GSA, IC GWAS 1 and NCI sets. Sex case only There were 709 female cases and 559 male cases in this analysis. 4 studies contributed to the case-only analysis. Only 2 studies contributed to the Case-Control by sex due to inability to retrieve sex from older control set files. Filters: variants with minor allele frequency < 0.01, Hardy-Weinberg P < 1×10⁻⁶ in controls, or imputation quality < 0.3 were removed before meta-analysis. Variants with heterogeneity across studies (Cochran’s Q P < 0.05) were excluded from this file. Format: positions are on GRCh38. Effects are reported for the effect allele (A1) relative to the reference allele (A2). Full column definitions and methods are in the accompanying README. Citation and contact: please cite the article above when using these data. Questions: Aubrey K. Hubbard (aubrey.hubbard@nih.gov); Mitchell J. Machiela (mitchell.machiela@nih.gov).